Remarkable Influence of α-SnWO4 Exposed Facets on Its Photocatalytic Performance for H2 and O2 Evolution Reactions

Harb, Moussab; Cavallo, Luigi; Basset, Jean-Marie

Remarkable Influence of α-SnWO4 Exposed Facets on Its Photocatalytic Performance for H2 and O2 Evolution Reactions

Files

Remarkable_acs.jpcc.0c06718.pdf (1.15 MB)

Embargo End Date

2021-07-31

Type

Article

Authors

Harb, Moussab

Cavallo, Luigi

Basset, Jean-Marie

KAUST Department

KAUST Catalysis Center (KCC)
Physical Science and Engineering (PSE) Division
Chemical Science Program

Online Publication Date

2020-07-30

Print Publication Date

2020-08-27

Date

2020-07-30

Abstract

A significant effect of the five major (121), (210), (111), (200), and (040) exposed facets obtained experimentally for orthorhombic α-SnWO4 material on its performance for photocatalytic water splitting is highlighted from a hybrid DFT-based comprehensive study. Their electronic, redox, and transport characteristics reveal significant anisotropic characters. The specific function of each surface in water oxidation and proton reduction is in direct relationship with the exposed W coordination number. Our study predicts the (210) facet as being the only possible good candidate for OER and HER upon surface modification, whereas the (200) facet is found a good candidate only for HER. The (121) facet is an acceptable candidate for both OER and HER and the (111) facet for HER only but less potentials than (210) and (200). The (040) facet is an unsuitable candidate neither for OER nor for HER. Interestingly, the proposed (001) facet is predicted to be the best candidate for HER. These results indicate the right direction to be followed for enhanced photocatalytic water splitting reactions based on a rational design of facet-oriented α-SnWO4 samples.

Citation

Harb, M., Cavallo, L., & Basset, J.-M. (2020). Remarkable Influence of α-SnWO4 Exposed Facets on Its Photocatalytic Performance for H2 and O2 Evolution Reactions. The Journal of Physical Chemistry C. doi:10.1021/acs.jpcc.0c06718

Acknowledgements

This research was supported by the King Abdullah University of Science and Technology (KAUST). The authors warmly acknowledge the KAUST Supercomputing Laboratory (KSL) for the CPU hours attributed to this work.